1. Field
The present invention relates to a method and system of restoring an image using a frequency-based image model, and more particularly, to a method and system of restoring an image using a frequency-based image model which can restore a low-resolution image into a high-resolution image.
2. Description of the Related Art
A technology of restoring a low-resolution image into a high-resolution image is used for an apparatus for facial recognition by restoring a low-resolution image of a human face into a high-resolution image of a human face since human faces photographed in a surveillance image are generally small and visually unidentifiable, an apparatus for restoring a broadcast image received at a low resolution in a digital television (DTV) into a high-resolution image, an apparatus for magnifying a military satellite photograph, and the like. Also, when a user intends to a desired portion from among images photographed by a digital camera, the digital camera uses a method of restoring a low-resolution image into a high-resolution image.
A high-resolution restoration method denotes a method of restoring the low-resolution image into the single high-resolution image basically using a low-resolution image pixel of each of a plurality of low-resolution images. The above-described method compensates for insufficient pixel information during restoration into the high-resolution image from a plurality of other low-resolution images. The high-resolution method typically includes Schultz's method, and Schultz's method is used for viewing a clear image by improving a picture quality of the image when viewed on TV. Basically, the low-resolution image is magnified as much as desired using a well-known interpolation method (for example, bi-cubic, and the like), and restoration of a portion inadequately reproduced in the magnified portion is performed using Bayesian Rule based on the plurality of low-resolution images.